Solving large scale linear programming problems

The interior point method (IPM) is now well established as a computationaly com-petitive scheme for solving very large scale linear programming problems. The leading variant of the IPM is the primal dual predictor corrector algorithm due to Mehrotra. The main computational efforts in this algorithm are the repeated calculation and solution of a large sparse positive definite system of equations. We describe an implementation of this algorithm for vector processors. At the heart of the implementation is a vectorized matrix multiplication and Cholesky factorization for sparse matrices. We identify the parts where vectorization can be beneficial and discuss in details the merits of alternative vectorization techniques. We show that the best way to utilize a vector processor is by exploiting dense computation within the sparse framework and by unrolling loop operations. We further present an extended definition of supernodes, and describe an implementation based on this new approach. We show that although this approach requires more memory it can increase the scope of dense computation substantially with out adding extra operations. Performance results on standard industrial test problems and comparison between an algorithm that utilizes the extended supernodes and one that utilizes standard supernodes are presented and discussed

Experimental investigations in combining primal dual interior point method and simplex based LP solvers

The use of a primal dual interior point method (PD) based optimizer as a robust linear programming (LP) solver is now well established. Instead of replacing the sparse simplex algorithm (SSX), the PD is increasingly seen as complementing it. The progress of PD iterations is not hindered by the degeneracy or the stalling problem of the SSX, indeed it reaches the 'near optimum' solution very quickly. The SSX algorithm, in contrast, is not affected by the boundary conditions which slow down the convergence of the PD. If the solution to the LP problem is non unique, the PD algorithm converges to an interior point of the solution set while the SSX algorithm finds an extreme point solution. To take advantage of the attractive properties of both the PD and the SSX, we have designed a hybrid framework whereby cross over from PD to SSX can take place at any stage of the PD optimization run. The cross over to SSX involves the partition of the PD solution set to active and dormant variables. In this paper we examine the practical difficulties in partitioning the solution set, we discuss the reliability of predicting the solution set partition before optimality is reached and report the results of combining exact and inexact prediction with SSX basis recovery

Solving large scale linear programming

The interior point method (IPM) is now well established as a competitive technique for solving very large scale linear programming problems. The leading variant of the interior point method is the primal dual - predictor corrector algorithm due to Mehrotra. The main computational steps of this algorithm are the repeated calculation and solution of a large sparse positive definite system of equations. We describe an implementation of the predictor corrector IPM algorithm on MasPar, a massively parallel SIMD computer. At the heart of the implemen-tation is a parallel Cholesky factorization algorithm for sparse matrices. Our implementation uses a new scheme of mapping the matrix onto the processor grid of the MasPar, that results in a more efficient Cholesky factorization than previously suggested schemes. The IPM implementation uses the parallel unit of MasPar to speed up the factorization and other computationally intensive parts of the IPM. An impor-tant part of this implementation is the judicious division of data and computation between the front-end computer, that runs the main IPM algorithm, and the par-allel unit. Performanc

Adapting the interior point method for the solution of LPs on serial, coarse grain parallel and massively parallel computers

In this paper we describe a unified scheme for implementing an interior point algorithm (IPM) over a range of computer architectures. In the inner iteration of the IPM a search direction is computed using Newton's method. Computationally this involves solving a sparse symmetric positive definite (SSPD) system of equations. The choice of direct and indirect methods for the solution of this system, and the design of data structures to take advantage of serial, coarse grain parallel and massively parallel computer architectures, are considered in detail. We put forward arguments as to why integration of the system within a sparse simplex solver is important and outline how the system is designed to achieve this integration

What is the therapeutic value of antidepressants in dementia? A narrative review

Objectives: Antidepressants are commonly used in dementia. Depression is a frequent and important co-morbidity in dementia and antidepressants are often used to treat depression and more widely. However there are questions about their utility in depression in dementia and other behavioural and psychological symptoms of dementia (BPSD). The aim of this narrative review is to summarise the evidence on whether there is therapeutic value in prescribing antidepressants to people with dementia. Methods: A PubMed search was performed to identify RCTs that prescribed antidepressants to people with dementia, either in the treatment of BPSD (depression, anxiety, agitation/aggression, psychosis, apathy) or for secondary outcomes (quality of life, carer burden, activities of daily living, cognition, clinical severity, adverse events). Results: Thirty-six RCTs were identified (participant n=3,386). A consistent finding in well-designed blinded placebo controlled trials in dementia is the lack of positive effect of antidepressants on outcomes of interest including depression. One large well-designed study has reported a significant reduction in agitation in people with dementia, but at the expense of clinically significant adverse events. Otherwise change observed in open trials is also seen in the placebo group, suggesting any effect is not attributable to the prescription of antidepressants. Conclusions: It is striking how few data there are on indications other than depression. We should question the use of antidepressants in dementia. Definitive trials of clinical effectiveness of specific indications such as anxiety and agitation in dementia and discontinuation of antidepressants in dementia are needed

Does the frequency of follow-up assessments affect clinical trial outcome? A meta-analysis and meta-regression of placebo-controlled randomized trials

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Monitoring and prevalence rates of metabolic syndrome in military veterans with serious mental illness

Background: Cardiovascular disease is the leading cause of mortality among patients with serious mental illness (SMI) and the prevalence of metabolic syndrome-a constellation of cardiovascular risk factors-is significantly higher in these patients than in the general population. Metabolic monitoring among patients using second generation antipsychotics (SGAs)-a risk factor for metabolic syndrome-has been shown to be inadequate despite the release of several guidelines. However, patients with SMI have several factors independent of medication use that predispose them to a higher prevalence of metabolic syndrome. Our study therefore examines monitoring and prevalence of metabolic syndrome in patients with SMI, including those not using SGAs. Methods and Findings: We retrospectively identified all patients treated at a Veterans Affairs Medical Center with diagnoses of schizophrenia, schizoaffective disorder or bipolar disorder during 2005-2006 and obtained demographic and clinical data. Incomplete monitoring of metabolic syndrome was defined as being unable to determine the status of at least one of the syndrome components. Of the 1,401 patients included (bipolar disorder: 822; schizophrenia: 222; and schizoaffective disorder: 357), 21.4% were incompletely monitored. Only 54.8% of patients who were not prescribed SGAs and did not have previous diagnoses of hypertension or hypercholesterolemia were monitored for all metabolic syndrome components compared to 92.4% of patients who had all three of these characteristics. Among patients monitored for metabolic syndrome completely, age-adjusted prevalence of the syndrome was 48.4%, with no significant difference between the three psychiatric groups. Conclusions: Only one half of patients with SMI not using SGAs or previously diagnosed with hypertension and hypercholesterolemia were completely monitored for metabolic syndrome components compared to greater than 90% of those with these characteristics. With the high prevalence of metabolic syndrome seen in this population, there appears to be a need to intensify efforts to reduce this monitoring gap

Adjunctive raloxifene treatment improves attention and memory in men and women with schizophrenia

There is increasing clinical and molecular evidence for the role of hormones and specifically estrogen and its receptor in schizophrenia. A selective estrogen receptor modulator, raloxifene, stimulates estrogen-like activity in brain and can improve cognition in older adults. The present study tested the extent to which adjunctive raloxifene treatment improved cognition and reduced symptoms in young to middle-age men and women with schizophrenia. Ninety-eight patients with a diagnosis of schizophrenia or schizoaffective disorder were recruited into a dual-site, thirteen-week, randomized, double-blind, placebocontrolled, crossover trial of adjunctive raloxifene treatment in addition to their usual antipsychotic medications. Symptom severity and cognition in the domains of working memory, attention/processing speed, language and verbal memory were assessed at baseline, 6 and 13 weeks. Analyses of the initial 6-week phase of the study using a parallel groups design (with 39 patients receiving placebo and 40 receiving raloxifene) revealed that participants receiving adjunctive raloxifene treatment showed significant improvement relative to placebo in memory and attention/processing speed. There was no reduction in symptom severity with treatment compared with placebo. There were significant carryover effects, suggesting some cognitive benefits are sustained even after raloxifene withdrawal. Analysis of the 13-week crossover data revealed significant improvement with raloxifene only in attention/processing speed. This is the first study to show that daily, oral adjunctive raloxifene treatment at 120 mg per day has beneficial effects on attention/processing speed and memory for both men and women with schizophrenia. Thus, raloxifene may be useful as an adjunctive treatment for cognitive deficits associated with schizophrenia.TW Weickert, D Weinberg, R Lenroot, SV Catts, R Wells, A Vercammen, M O, Donnell, C Galletly, D Liu, R Balzan, B Short, D Pellen, J Curtis, VJ Carr, J Kulkarni, PR Schofield and CS Weicker

Music therapy and weight gain in preterm infants: Secondary analysis of the randomized controlled LongSTEP trial

Objectives This study assessed the association between MT and weight gain among preterm infants hospitalized in Neonatal Intensive Care Units. Methods Data collected during the international, randomized, Longitudinal Study of Music Therapy's Effectiveness for Premature Infants and their Caregivers (LongSTEP) study were compared between the MT group and the standard care (SC) group. Weights were recorded at birth, enrollment, and discharge. Weight percentiles, Z-scores, weight gain velocity, and extrauterine growth restriction (EUGR) were calculated. Results Among 201 preterm infants included, no significant differences in weight parameters (weight, weight percentiles, weight Z-scores; all p ≥ 0.23) were found between the MT group (n = 104) and the SC (n = 97) group at birth, enrollment, or discharge. No statistical differences in EUGR represented by change in Z-scores from birth to discharge were recorded between MT and SC (0.8 vs. 0.7). Among perinatal parameters, younger gestational age (p = 0.005) and male sex (p = 0.012) were associated with increased risk of EUGR at discharge. Antenatal steroid treatment, systemic infection, bronchopulmonary dysplasia, neurological morbidities, retinopathy of prematurity, necrotizing enterocolitis, parental factors (amount of skin-to-skin care, bonding, anxiety, and depression questionnaire scores), and type of enteral nutrition did not significantly influence weight gain parameters (all p > 0.05). Conclusions In the LongSTEP study, MT for preterm infants and families was not associated with better weight parameters compared to the SC group. The degree of prematurity remains the main risk factor for unfavorable weight parameters.publishedVersio